Using multi‐criteria decision analysis for assessing sustainability of agricultural systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Composite indicators for six key categories of agricultural sustainability are utilized within a Multi‐Criteria Decision Analysis (MCDA) structure to assess and compare the sustainability of different agricultural systems. Individual indicators – productivity, stability, efficiency, durability, compatibility and equity – were used to develop composite indicators. In this research, the major steps used to obtain the aggregated indicators and assess sustainability are: define sustainability; recognize sustainability issues; identify indicators; categorize sustainability; measure indicator values to develop composite indicators; give weighting to the categories of sustainability; aggregate composite indicators; and compare the sustainability of different agricultural systems. Using composite indicators, an MCDA structure is employed to evaluate and rank the agricultural systems of southwest coastal Bangladesh in terms of the level of agricultural sustainability of each one. The case study demonstrates that this MCDA approach has the potential to become a useful framework for agricultural sustainability assessment.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it